An Evaluation of Risk Factors for Patient "No Shows" at an Urban Joint Arthroplasty Clinic

Predictors of No-Shows and Cancellations in an Outpatient Neuropsychology Clinic in a Large Healthcare System

BACKGROUND

The purpose of this study was to evaluate potential predictors of no-shows and late cancellations in an outpatient clinic within a large healthcare system serving vulnerable communities.

METHODS

Demographic data and appointment status were recorded for 537 consecutive patients scheduled for neuropsychological evaluation in an outpatient psychiatry clinic. Patients include 220 males and 317 females with an average formal education of 11.01 years (SD = 3.87) and age of 55.64 years (SD = 16.20).

RESULTS

The overall rate of no-shows or late cancellations was 20%. Of the 106 patients who no-showed/late cancelled, 41% rescheduled, and of those, 23% missed or late cancelled their second appointment. No-shows and late cancellations were associated with historical/prior no-show rate, while race/ethnicity and activation of MyChart had slight impacts.

CONCLUSIONS

These data suggest that prior no-show rates and MyChart access may be targets for interventions to improve show rates. This is important for the patients' gaining access to care as well as minimizing financial strains for the system and increasing wait times/delays to care for other patients.

Barriers Associated With Missed Palliative Care Telehealth Visits

Background: The COVID-19 pandemic accelerated the adoption of telehealth in palliative care. While this technology showed efficiencies in healthcare delivery, it also unmasked inequalities affecting the socially disadvantaged. Objective: To identify factors associated with missed telehealth visits. Methods: We reviewed telehealth visits between April 1, 2020 and March 31, 2021 at a palliative care clinic. Disease-related and demographic information were recorded, including residency in community outreach zones (COZ)-zip code clusters known for healthcare underutilization. We categorized patients with at least one missed visit as "any miss" (AM), and those with at least three scheduled visits and missed at least 50% as "pattern miss" (PM). Results: Of 1225 scheduled telehealth (i.e., audiovisual) visits, there were 802 completed, 52 missed initial and 371 missed follow-up encounters. Among 505 unique patients, 363 (72%) were receiving cancer treatment, 170 (34%) had multiple insurance, 87 (17%) lived in COZ, 101 (20%) were AM, and 27 (5%) were PM. Patients in COZ had significantly higher risk of PM vs those outside (OR = 2.56, 95% CI: 1.06-5.78, P = .03). Patients with multiple insurance had significantly higher risk of PM vs those with single or no coverage (OR = 3.06, 95% CI: 1.40-6.93, P = .006). Patients on treatment had significantly higher risk of AM vs those not in treatment (OR = 1.75, 95% CI: 1.05-3.06, P = .04). Conclusion: We identified living in areas with healthcare underutilization, active cancer treatment, and multiple insurance coverage as barriers to telehealth visits. Measures are necessary to attenuate disparities in accessing palliative care via telehealth.

Is Limited English Proficiency Associated With Differences in Care Processes and Treatment Outcomes in Patients Undergoing Orthopaedic Surgery? A Systematic Review

BACKGROUND

Approximately 25 million people in the United States have limited English proficiency. Current developments in orthopaedic surgery, such as the expansion of preoperative education classes or patient-reported outcome collection in response to bundled payment models, may exacerbate language-related barriers. Currently, there are mixed findings of the associations between limited English proficiency and care processes and outcomes, warranting a cross-study synthesis to identify patterns of associations.

QUESTIONS/PURPOSES

In this systematic review, we asked: Is limited English proficiency associated with (1) differences in clinical care processes, (2) differences in care processes related to patient engagement, and (3) poorer treatment outcomes in patients undergoing orthopaedic surgery in English-speaking countries?

METHODS

On June 9, 2023, a systematic search of four databases from inception through the search date (PubMed, Ovid Embase, Web of Science, and Scopus) was performed by a medical librarian. Potentially eligible articles were observational studies that examined the association between limited English proficiency and the prespecified categories of outcomes among pediatric and adult patients undergoing orthopaedic surgery or receiving care in an orthopaedic surgery setting. We identified 10,563 records, of which we screened 6966 titles and abstracts after removing duplicates. We reviewed 56 full-text articles and included 29 peer-reviewed studies (outcome categories: eight for clinical care processes, 10 for care processes related to patient engagement, and 15 for treatment outcomes), with a total of 362,746 patients or encounters. We extracted data elements including study characteristics, definition of language exposure, specific outcomes, and study results. The quality of each study was evaluated using adapted Newcastle-Ottawa scales for cohort or cross-sectional studies. Most studies had a low (48%) or moderate (45%) risk of bias, but two cross-sectional studies had a high risk of bias. To answer our questions, we synthesized associations and no-difference findings, further stratified by adjusted versus unadjusted estimates, for each category of outcomes. No meta-analysis was performed.

RESULTS

There were mixed findings regarding whether limited English proficiency is associated with differences in clinical care processes, with the strongest adjusted associations between non-English versus English as the preferred language and delayed ACL reconstruction surgery and receipt of neuraxial versus general anesthesia for other non-Spanish versus English primary language in patients undergoing THA or TKA. Limited English proficiency was also associated with increased hospitalization costs for THA or TKA but not opioid prescribing in pediatric patients undergoing surgery for fractures. For care processes related to patient engagement, limited English proficiency was consistently associated with decreased patient portal use and decreased completion of patient-reported outcome measures per adjusted estimates. The exposure was also associated with decreased virtual visit completion for other non-Spanish versus English language and decreased postoperative opioid refill requests after TKA but not differences in attendance-related outcomes. For treatment outcomes, limited English proficiency was consistently associated with increased hospital length of stay and nonhome discharge per adjusted estimates, but not hospital returns. There were mixed findings regarding associations with increased complications and worse postoperative patient-reported outcome measure scores.

CONCLUSION

Findings specifically suggest the need to remove language-based barriers for patients to engage in care, including for patient portal use and patient-reported outcome measure completion, and to identify mechanisms and solutions for increased postoperative healthcare use. However, interpretations are limited by the heterogeneity of study parameters, including the language exposure. Future research should include more-precise and transparent definitions of limited English proficiency and contextual details on available language-based resources to support quantitative syntheses.

LEVEL OF EVIDENCE

Level III, therapeutic study.

Factors associated with non-adherence to dual-energy x-ray absorptiometry screening during the COVID-19 pandemic in an academic medical center

This study explored why some elderly females do not adhere to their bone density tests. It found that factors like age, race, marital status, insurance type, social vulnerability index, and vaccination status influence completion of these tests. Addressing these differences could improve the management of bone health in older adults.

PURPOSE

This study investigated factors influencing the cancellation of dual-energy x-ray absorptiometry (DXA) scans among females aged 65 and above during the COVID-19 pandemic.

METHODS

Utilizing a dataset of 19,066 females from 2021 to 2023, the research employed chi-squared tests and logistic regression analyses to examine demographic, socio-economic, and health-related determinants of DXA scan adherence.

RESULTS

Key findings revealed that younger seniors, White patients, married individuals, those with commercial/private or Medicare insurance, and vaccinated persons were more likely to complete DXA scans. In contrast, Asian and African American females, along with those from higher Social Vulnerability Index areas, showed lower completion rates.

CONCLUSION

These results highlight the need for tailored strategies to improve osteoporosis screening adherence, focusing on identified demographic groups to enhance overall healthcare outcomes in osteoporosis management.

Patient "No-Show" Increases the Risk of 90-Day Complications Following Primary Total Knee Arthroplasty: A Retrospective Cohort Study of 6,776 Patients

BACKGROUND

Patients who "no-show" (NS) clinical appointments are at a high risk of adverse health outcomes. The objective of this study was to evaluate and characterize the relationship between NS visits prior to primary total knee arthroplasty (TKA) and 90-day complications after TKA.

METHODS

We retrospectively reviewed 6,776 consecutive patients undergoing primary TKA. Study groups were separated based on whether patients who NS versus always attended their appointment. A NS was defined as an intended appointment that was not canceled or rescheduled ≤2 hours before the appointment in which the patient did not show. Data collected included total number of follow-up appointments prior to surgery, patient demographics, comorbidities, and 90-day postoperative complications.

RESULTS

Patients who have ≥3 NS appointments had 1.5 times increased odds of a surgical site infection (odds ratio (OR) 1.54, P = .002) compared to always attended patients. Patients who were ≤65 years old (OR: 1.41, P < .001), smokers (OR: 2.01, P < .001), and had a Charlson comorbidity index ≥3 (OR: 4.48, P < .001) were more likely to miss clinical appointments.

CONCLUSION

Patients who have ≥3 NS appointments prior to TKA had an increased risk for surgical site infection. Sociodemographic factors were associated with higher odds of missing a scheduled clinical appointment. These data suggest that orthopaedic surgeons should consider NS data as an important clinical decision-making tool to assess risk for postoperative complications to minimize complications following TKA.

Racial, Ethnic, and Socioeconomic Disparities Drive Appointment No-Show in Patients with Chronic Eye Disease

BACKGROUND

Visit no-shows (NS) reduce clinic efficiency and effective resource allocation. Inadequate follow-up among patients with chronic eye disease increases risk of disease progression. Our study identifies demographic, medical, and socioeconomic characteristics that increase odds of NS among patients with chronic eye conditions at high risk of vision-threatening complications.

METHODS

This is a retrospective case-control study of data abstracted over a 5-year period (January 2013-December 2018) in an urban academic ophthalmology practice. Follow-up appointments of patients ≥ 18 years of age with a diagnosis of glaucoma, diabetic retinopathy, or age-related macular degeneration were included. Age, sex, race, ethnicity, language preference, zip code, and relevant medical history were recorded. A multivariate mixed logistic regression model was utilized to determine any association between demographic factors and visit NS.

RESULTS

A total of 106,652 visits for 4,598 unique patients were included in this study. Of these, 13,240 (12.4%) visits were NS. Patient characteristics that increased the odds of NS included Hispanic ethnicity (p < 0.0001), Black race (p < 0.0001), and a history of mental illness (p < 0.0001). Socioeconomic factors that increased the odds of NS included median household income < $40,000 (p = 0.002), Medicare insurance (p < 0.0001), and Medicaid insurance (p < 0.0001).

CONCLUSIONS

Our results highlight the influence of ethnic, racial, medical, and socioeconomic characteristics on appointment NS among patients with chronic eye disease. Future interventions aimed at reducing appointment NS could channel resources to the at-risk populations identified in this analysis to improve access to care for those who need it most.

Application of a Machine Learning Algorithm to Develop and Validate a Prediction Model for Ambulatory Non-Arrivals

BACKGROUND

Non-arrivals to scheduled ambulatory visits are common and lead to a discontinuity of care, poor health outcomes, and increased subsequent healthcare utilization. Reducing non-arrivals is important given their association with poorer health outcomes and cost to health systems.

OBJECTIVE

To develop and validate a prediction model for ambulatory non-arrivals.

DESIGN

Retrospective cohort study.

PATIENTS OR SUBJECTS

Patients at an integrated health system who had an outpatient visit scheduled from January 1, 2020, to February 28, 2022.

MAIN MEASURES

Non-arrivals to scheduled appointments.

KEY RESULTS

There were over 4.3 million ambulatory appointments from 1.2 million adult patients. Patients with appointment non-arrivals were more likely to be single, racial/ethnic minorities, and not having an established primary care provider compared to those who arrived at their appointments. A prediction model using the XGBoost machine learning algorithm had the highest AUC value (0.768 [0.767-0.770]). Using SHAP values, the most impactful features in the model include rescheduled appointments, lead time (number of days from scheduled to appointment date), appointment provider, number of days since last appointment with the same department, and a patient's prior appointment status within the same department. Scheduling visits close to an appointment date is predicted to be less likely to result in a non-arrival. Overall, the prediction model calibrated well for each department, especially over the operationally relevant probability range of 0 to 40%. Departments with fewer observations and lower non-arrival rates generally had a worse calibration.

CONCLUSIONS

Using a machine learning algorithm, we developed a prediction model for non-arrivals to scheduled ambulatory appointments usable for all medical specialties. The proposed prediction model can be deployed within an electronic health system or integrated into other dashboards to reduce non-arrivals. Future work will focus on the implementation and application of the model to reduce non-arrivals.

The utility of machine learning algorithms for the prediction of patient-reported outcome measures following primary hip and knee total joint arthroplasty

BACKGROUND

Patient-reported outcome measures (PROMs) are increasingly used as quality benchmark in total hip and knee arthroplasty (THA; TKA) due to bundled payment systems that aim to provide a patient-centered, value-based treatment approach. However, there is a paucity of predictive tools for postoperative PROMs. Therefore, this study aimed to develop and validate machine learning models for the prediction of numerous patient-reported outcome measures following primary hip and knee total joint arthroplasty.

METHODS

A total of 4526 consecutive patients (2137 THA; 2389 TKA) who underwent primary hip and knee total joint arthroplasty and completed both pre- and postoperative PROM scores was evaluated in this study. The following PROM scores were included for analysis: HOOS-PS, KOOS-PS, Physical Function SF10A, PROMIS SF Physical and PROMIS SF Mental. Patient charts were manually reviewed to identify patient demographics and surgical variables associated with postoperative PROM scores. Four machine learning algorithms were developed to predict postoperative PROMs following hip and knee total joint arthroplasty. Model assessment was performed through discrimination, calibration and decision curve analysis.

RESULTS

The factors most significantly associated with the prediction of postoperative PROMs include preoperative PROM scores, Charlson Comorbidity Index, American Society of Anaesthesiology score, insurance status, age, length of hospital stay, body mass index and ethnicity. The four machine learning models all achieved excellent performance across discrimination (AUC > 0.83), calibration and decision curve analysis.

CONCLUSION

This study developed machine learning models for the prediction of patient-reported outcome measures at 1-year following primary hip and knee total joint arthroplasty. The study findings show excellent performance on discrimination, calibration and decision curve analysis for all four machine learning models, highlighting the potential of these models in clinical practice to inform patients prior to surgery regarding their expectations of postoperative functional outcomes following primary hip and knee total joint arthroplasty.

LEVEL OF EVIDENCE

Level III, case control retrospective analysis.

Telemedicine and Socioeconomics in Orthopaedic Trauma Patients: A Quasi-Experimental Study During the COVID-19 Pandemic

INTRODUCTION

Socioeconomic factors may introduce barriers to telemedicine care access. This study examines changes in clinic absenteeism for orthopaedic trauma patients after the introduction of a telemedicine postoperative follow-up option during the COVID-19 pandemic with attention to patient socioeconomic status (SES).

METHODS

Patients (n = 1,060) undergoing surgical treatment of pelvic and extremity trauma were retrospectively assigned to preintervention and postintervention cohorts using a quasi-experimental design. The intervention is the April 2020 introduction of a telemedicine follow-up option for postoperative trauma care. The primary outcome was the missed visit rate (MVR) for postoperative appointments. We used Poisson regression models to estimate the relative change in MVR adjusting for patient age and sex. SES-based subgroup analysis was based on the Area Deprivation Index (ADI) according to home address.

RESULTS

The pre-telemedicine group included 635 patients; the post-telemedicine group included 425 patients. The median MVR in the pre-telemedicine group was 28% (95% confidence interval [CI], 10% to 45%) and 24% (95% CI, 6% to 43%) in the post-telemedicine group. Low SES was associated with a 40% relative increase in MVR (95% CI, 17% to 67%, P < 0.001) compared with patients with high SES. Relative MVR changes between pre-telemedicine and post-telemedicine groups did not reach statistical significance in any socioeconomic strata (low ADI, -6%; 95% CI, -25% to 17%; P = 0.56; medium ADI, -18%; 95% CI, -35% to 2%; P = 0.07; high ADI, -12%; 95% CI, -28% to 7%; P = 0.20).

CONCLUSIONS

Low SES was associated with a higher MVR both before and after the introduction of a telemedicine option. However, no evidence in this cohort demonstrated a change in absenteeism based on SES after the introduction of the telemedicine option. Clinicians should be reassured that there is no evidence that telemedicine introduces additional socioeconomic bias in postoperative orthopaedic trauma care.

LEVEL OF EVIDENCE

III.

Impact of Patient Socioeconomic Disparities on Time to Tympanostomy Tube Placement

OBJECTIVES

Extensive literature exists documenting disparities in access to healthcare for patients with lower socioeconomic status (SES). The objective of this study was to examine access disparities and differences in surgical wait times in children with the most common pediatric otolaryngologic surgery, tympanostomy tubes (TT).

METHODS

A retrospective cohort study was performed at a tertiary children's hospital. Children ages <18 years who received a first set of tympanostomy tubes during 2015 were studied. Patient demographics and markers of SES including zip code, health insurance type, and appointment no-shows were recorded. Clinical measures included risk factors, symptoms, and age at presentation and first TT.

RESULTS

A total of 969 patients were included. Average age at surgery was 2.11 years. Almost 90% were white and 67.5% had private insurance. Patients with public insurance, ≥1 no-show appointment, and who lived in zip codes with the median income below the United States median had a longer period from otologic consult and preoperative clinic to TT, but no differences were seen in race. Those with public insurance had their surgery at an older age than those with private insurance (P < .001) and were more likely to have chronic otitis media with effusion as their indication for surgery (OR: 1.8, 95% CI: 1.2-2.5, P = .003).

CONCLUSIONS

Lower SES is associated with chronic otitis media with effusion and a longer wait time from otologic consult and preoperative clinic to TT placement. By being transparent in socioeconomic disparities, we can begin to expose systemic problems and move forward with interventions.

LEVEL OF EVIDENCE

4.